The Eco-cast

This post is a follow-up to my ecological forecasting post last month. The work that I presented at the Ocean Sciences meeting was built around the idea of producing forecasts of ecosystems. Much of what I presented was discussed in that post, so I'd just like to take a little space here to build on the vision.

I think about ecosystem forecasts as close analogues to weather forecasts. There are, of course, important differences, but I'll save that discussion for a later post. Here I'll focus on the analogy.

Early weather predictions were based on signs and signals from the immediate surroundings, and on past observations. These observations were interwoven with ecological ones as well. People have probably been making these sorts of predictions since the first homo sapiens scratched their heads and gazed upon a bold red sunset. Unfortunately, these first people left nothing to cite, so we'll have to do what we usually do, and refer to Aristotle on the matter.

Aristotle included many guidelines for weather prediction in Meteorologica, but actually my favorite work on the matter is Theophrastus' The Book of Signs. For centuries, predictions were made by following signs like this one, taken from The Book of Signs:

"It is a sign of rain when a tame duck gets under the eaves and flaps its wings."

In the 20th century, scientists began using computers to make forecasts. In the 1950s, the first computational forecasts were inferior to the more subjective, duck-watching methods. Computer models would suddenly predict an army of cyclones marching across the country. You would probably produce a better forecast by just saying, "Tomorrow's weather will be pretty much like today's."

Yet there was intense optimism regarding the potential of computational prediction. John von Neumann, one of the great scientists of the century, stated:

This was followed by decades of steady improvement. Computational weather forecasts are now the norm. While we do complain when meteorologists get it wrong, I think it's clear that today's forecasts have immense value and are a crucial part of how our society operates.

Von Neumann's vision, however, has not been realized. One contributing factor was the discovery of what is termed "chaos". Without going into too much detail, I'll just say that mathematicians discovered fundamental limits on the predictability of certain mathematical systems, including weather and ecosystems. As the founder, Edward Lorenz, phrased it:

"Predictability: Does the flap of a butterfly's wings in Brazil set off a tornado in Texas?"

Nevertheless, with better and better computers and techniques, scientists continue to improve weather prediction. A testament to their utility is the ubiquity of weather forecasts in our day to day lives. This history provides good context for the development of ecosystem forecasting. With steadily improving models and increasing monitoring, we are poised to transition from the more subjective and sign-based forecasts to more precise computational forecasts. Naturally, it will be some time before we're forecasting at the level of meteorologists, but one day in the future, you might be watching a broadcaster like this on your daily news: